Simulation of fragmental rockfalls detected using

Nat. Hazards Earth Syst. Sci., 19, 2385–2404, 2019
https://doi.org/10.5194/nhess-19-2385-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Simulation of fragmental rockfalls detected using terrestrial laser
scans from rock slopes in south-central
British Columbia, Canada
Zac Sala1,2, D. Jean Hutchinson1, and Rob Harrap1
1Department of Geological Sciences and Geological Engineering, Queen’s University,
Kingston, K7L 3N6, Canada
2BGC Engineering Inc., Vancouver, V6Z 0C8, Canada
Correspondence: Zac Sala ([email protected])
Received: 29 October 2018 – Discussion started: 24 January 2019
Revised: 18 July 2019 – Accepted: 25 July 2019 – Published: 30 October 2019
Abstract. Rockfall presents an ongoing challenge to the safe
operation of transportation infrastructure, creating hazardous
conditions which can result in damage to roads and railways,
as well as loss of life. Rockfall risk assessment frameworks
often involve the determination of rockfall runout in an at-
tempt to understand the likelihood that rockfall debris will
reach an element at risk. Rockfall modelling programs which
simulate the trajectory of rockfall material are one method
commonly used to assess potential runout. This study aims to
demonstrate the effectiveness of a rockfall simulation proto-
type which uses the Unity 3D game engine. The technique is
capable of simulating rockfall events comprised of many mo-
bile fragments, a limitation of many industry standard rock-
fall modelling programs. Five fragmental rockfalls were sim-
ulated using the technique, with slope and rockfall geome-
tries constructed from high-resolution terrestrial laser scans.
Simulated change detection was produced for each of the
events and compared to the actual change detection results
for each rockfall as a basis for testing model performance.
In each case the simulated change detection results aligned
well with the actual observed change in terms of location and
magnitude. An example of how the technique could be used
to support the design of rockfall catchment ditches is shown.
Suggestions are made for future development of the simu-
lation technique with a focus on better informing simulated
rockfall fragment size and the timing of fragmentation.
1 Introduction
Rockfall is a mass-movement hazard often found in moun-
tainous environments, posing risk to human lives and the safe
operation of infrastructure. In Canada, rockfall hazard is par-
ticularly problematic for transportation infrastructure, where
traffic corridors have been constructed in steep river valleys,
adjacent to natural and cut slopes. In many of these valleys,
right-of-way space is limited, forcing operators to construct
highways and railways with minimal clearance to potentially
unstable rock masses. The proximity and extensive presence
of fractured and weathered rock slopes, combined with the
seemingly unpredictable nature of rockfall events, makes it
difficult for operators to manage this hazard.
Like any geohazard, we are interested in knowing how fre-
quently we can expect events to occur, where they are most
likely to come from, and whether or not they will reach and
cause harm to our elements at risk. For rockfall this could
involve identifying lithologies which are more susceptible to
rockfall (e.g. Rosser et al., 2005; van Veen, 2016) or corre-
lating rockfall frequency to triggering events like severe rain
storms (e.g. D’Amato et al., 2016; Pratt et al., 2018). In order
to build these relationships, we first need knowledge of pre-
vious rockfall in the area. This is one of the main challenges
in the study of rockfall. Due to challenging terrain in moun-
tainous areas, and safety concerns where rockfall activity is
high, site access to the slopes of interest is often limited, pro-
hibiting direct measurement.
In order to circumvent these obstacles, modern remote
sensing techniques, such as lidar, have seen widespread use
Published by Copernicus Publications on behalf of the European Geosciences Union.

2386 Z. Sala et al.: Simulation of fragmental rockfalls detected using terrestrial laser scans
in the study of landslide hazards like rockfall (Jaboyedoff
et al., 2012). Terrestrial laser scanning (TLS) in particular
has been increasingly applied in recent years to the study
of rock slope instabilities (Abellán et al., 2014; e.g. Lato et
al., 2009, 2015; Kromer et al., 2017). TLS provides a de-
tailed 3-D model of the slope geometry, supporting a range
of geotechnical and geomechanical analyses. From a single
scan we can extract slope angle measurements, map rock
mass structure and look for evidence of past rockfall (Telling
et al., 2017). Using multiple successive scans of the same
slope, progressive changes to the slope surface can be mea-
sured. Multi-temporal scanning enables researchers to de-
tect rockfall events over time and build detailed magnitude–
frequency relationships for slopes, supporting the study of
processes such as coastal cliff erosion (e.g. Rosser et al.,
2007; Williams et al., 2018), as well as hazard and risk
assessments for linear infrastructure such as railways (e.g.
van Veen et al., 2017). The identification of rockfall events
using sequential scans also permits the back analysis of
rockfall-triggering factors and failure mechanisms. A study
by Kromer et al. (2015) used TLS change detection to in-
vestigate the occurrence of a 2600 m3failure above a section
of the Canadian National (CN) Railway in western Canada,
including an analysis of structural constraints, pre-failure de-
formation, and precursor rockfall leading up to failure.
While the application of TLS to rock slope monitoring is
often focused on determining how likely future rockfall is or
where the rockfall may come from, it is also important to de-
termine how likely it is that the rockfall material will reach
an element at risk should a fall occur. In order to answer that
question, rockfall modelling programs can be used to simu-
late the runout of falling rock material using numerical mod-
els (Turner and Duffy, 2012). A rockfall simulation requires
a representation of the slope surface and rockfall mass being
modelled in 2-D, 2.5-D, or 3-D. TLS can support rockfall
simulation by providing a high-resolution 3-D model of the
slope surface and, in cases where a rockfall event has been
identified using change detection between multiple scans, the
volume and location of the rockfall mass. In order to make
use of the quality and quantity of 3-D point cloud data be-
ing collected as part of a rock slope monitoring program
in western Canada, a 3-D rockfall simulation technique us-
ing game-engine technology has been developed (Ondercin,
2016; Sala, 2018). The technique uses the video game devel-
opment platform Unity 3D (Unity Technologies, 2018) and is
capable of simulating rockfall runout using fully 3-D meshes
built from TLS point cloud data.
One of the strengths of this simulation technique is its abil-
ity to simulate rockfall runout using numerous interacting
bodies. This capability allows us to produce simulations of
fragmental rockfall events, which are defined by the presence
of multiple mobile fragments of rock during runout (Hungr
and Evans, 1988). Conventional rockfall modelling programs
(e.g. RocFall, Rocscience Technologies, 2016; Rockyfor3D,
Dorren, 2015; RAMMS:ROCKFALL, Bartelt et al., 2016)
simulate single boulder trajectories at a time and there-
fore are unable to model fragmental rockfall runout. Efforts
to model fragmental rockfall processes, including the dis-
aggregation of falling rock masses along pre-existing dis-
continuities, or the breakage of intact blocks during im-
pact, have been demonstrated by previous authors. Cuervo
et al. (2015) utilized a discrete element technique to model
the disaggregation of a 1000 m3rockfall event in southern
France comprised of numerous mobile fragments. Wang and
Tonon (2011) developed a discrete element code which mod-
els the fragmentation of a falling rock at impact, taking into
consideration the effect of impact velocity, ground condition,
energy loss, and fracture properties such as persistence. The
GIS-based tool RockGIS, presented in Matas et al. (2017),
incorporates both breakage along pre-existing discontinuities
and the generation of new fragments during impact into a 3-
D runout modelling program and has been utilized to model a
10 000 m3fragmental rockfall in the eastern Pyrenees moun-
tains. The goal of the work presented in this paper is to
demonstrate the capability of our novel game-engine-hosted
simulation technique to model a series of rockfall events
detected using TLS change detection at two rock slopes in
south-central British Columbia. Emphasis is placed on the
ability of the technique to be used for fragmental rockfall
runout simulation, including a discussion of how these types
of simulation could support mitigation design.
2 Study sites
The rock slopes of focus for this paper are part of the
Ashcroft subdivision of the CN Railway. The subdivision
follows sections of the Thompson and Fraser River valleys,
located between the towns of Ashcroft and Lytton, British
Columbia. This region serves as an important transporta-
tion corridor for Canada, with the presence of the CN Rail
mainline, as well as sections of the Canadian Pacific Rail-
way, and the Trans-Canada Highway. A previous study by
Piteau (1977) identified that rock cuts in this region are sub-
ject to slope instability issues due to a combination of lat-
eral erosion from river activity, over-steepening from blast-
ing during the construction of the railways, and a lack of ad-
equate rockfall catchment areas.
Two sites in the Ashcroft subdivision will form the basis
for this research, White Canyon and Goldpan. The location
of these sites along the Thompson River and proximity to the
town of Lytton, BC, can be seen in Fig. 1. The monitoring of
these slopes is part of the Railway Ground Hazard Research
Program, a collaborative research initiative focused on the
characterization and assessment of mass movement hazards
affecting Canadian railways.
Data collection in the Ashcroft subdivision first took place
in 2012, and regular monitoring at both sites has been ongo-
ing since 2014, with data collection taking place on a sea-
sonal basis, approximately every 3 months. Point cloud data
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Z. Sala et al.: Simulation of fragmental rockfalls detected using terrestrial laser scans 2387
Figure 1. Aerial imagery showing the location of the White Canyon
and Goldpan field sites situated along the Thompson River, near the
town of Lytton in south-central British Columbia. This region is
approximately 160 km northeast of the city of Vancouver. (Image
source: © Google Earth; Digital Globe 2018.)
collection consists of TLS scans acquired using an Optech
ILRIS 3D-ER (2012–2017) or Riegl VZ-400i (2018) lidar
system. Additionally, aerial laser scan (ALS) data coverage
for both sites, with an average point spacing of 0.3 m, was
acquired in 2014 and 2015. Site photos are collected using
a Nikon D700 or similar camera with a 135 mm prime lens.
A series of photos of the slope are taken using a GigaPan
EPIC Pro robotic camera mount and stitched together into
a single high-resolution site panorama using GigaPan Stitch
(GigaPan Systems, 2013).
Goldpan is located on the north side of the Thompson
River, approximately 26 km upstream from the town of Lyt-
ton. Present at the base of the slope is a section of the CN Rail
main line. The rock slope spans 800 m, rising up to 65 m ver-
tically above track level. The average slope angle at the site is
55–60◦. TLS data are collected from scanning vantage points
across the river from the slope, accessed via Goldpan Provin-
cial Park. Scan distances range between 170 and 230 m, pro-
ducing an average point spacing of approximately 6 cm.
White Canyon is located on the north side of the Thomp-
son River, approximately 5 km upstream from the town of
Lytton. Present at the base of the slope is a section of the
CN Rail main line. The rock slope spans 2.4 km, rising up to
375 m vertically above track level. The average slope angle at
the site is 40–45◦. TLS data are collected from scanning van-
tage points across the river from the slope. Scan distances
range between 400 and 600 m, producing an average point
spacing of approximately 10 cm.
Goldpan and White Canyon are located in the Inter-
montane belt of the Canadian Cordillera. Both sites be-
long to the Quesnellia volcanic arc terrane, which is com-
posed of Carboniferous to mid-Jurassic volcanic, sedimen-
tary, and plutonic rocks (Struik, 1987; Monger and Nokel-
berg, 1996). The rock mass at Goldpan is largely mas-
sive and is predominantly composed of volcanics of the
mid-Cretaceous Kingsvale–Spences Bridge Group. The main
rock types of this group are basaltic to andesitic flows inter-
spersed with volcaniclastic sandstones, shales, and conglom-
erates (Brown, 1981). The comparatively large rock slope of
White Canyon belongs to the Mt Lytton plutonic complex
(Greig, 1989). Locally, the dominant rock type is an amphi-
bolite grade quartzofeldspathic gneiss. Amphibolite band-
ing is also present and gneissic layering is crosscut through-
out the canyon by intrusive phases of gabbro, tonalite, and
granodiorite (Brown, 1981). Preferential weathering around
these intrusions often results in the formation of vertical rock
spires which act as source zones for rockfall.
Mitigative measures at both sites have been installed in
response to frequent rockfall activity impacting railway op-
erations. At Goldpan this includes rockfall wire mesh draped
over parts of the slope, extensive sections of shotcrete, and
four concrete rock sheds. In the eastern half of White Canyon
there are two timber rock sheds and one concrete shed, as
well as wire mesh rockfall nets and concrete lock blocks ad-
jacent to the track. The western half of White Canyon also
has wire mesh rockfall nets and lock block retaining walls,
as well as an additional three concrete rock sheds and one
timber rock shed. Slide detector fences are present at both
sites, comprised of horizontal wires strung between upright
telephone poles, and provide warning by switching the track
signal to stop when broken.
3 Rockfall events
Five rockfall events were selected from a database of rock-
falls which have been identified using change detection at
White Canyon West, White Canyon East, and Goldpan since
2012 (Kromer et al., 2015). These events have masses rang-
ing from 2 to 170 m3, exhibiting a combination of struc-
turally controlled failure modes including wedge sliding, pla-
nar sliding, toppling, and overhanging blocks. Images of the
five slope sections where the rockfall events of interest took
place can be seen in Fig. 2.
Each event showed material accumulation below the
source zone in the change detection results. This is essen-
tial information for comparison with our simulation results.
Each event is also close to track level, with the highest fall
occurring 46 m vertically above the track. These events were
selected because the shorter distance from source to a notable
accumulation of material presents a simpler trajectory for
back analysis and reduces potential confusion in interpreting
whether the material gain is due to the selected rockfall or an-
other mass-movement nearby. In each case, change was de-
tected using the Multiscale Model to Model Cloud Compar-
ison (M3C2) point–point distance calculation (Lague et al.,
2013) in CloudCompare (2018), between the pre- and post-
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2388 Z. Sala et al.: Simulation of fragmental rockfalls detected using terrestrial laser scans
Figure 2. Photos of five rock slope sections, prior to failure, from
the Goldpan (a) and White Canyon (b–e) sites adjacent to the CN
Railway. The red regions indicate the source zone for the rockfall
events discussed in this paper.
fall TLS scans. A summary of each of the rockfall events
including change detection results, and site photos before
and after the event, is provided in Figs. 3–7. Discontinuity
and slope angle measurements used for the stereonet failure
mode analysis shown in each figure were completed using
the Compass tool in CloudCompare.
3.1 Event fragmentation
While the selected rockfall events were not observed directly,
each rockfall is believed to have been comprised of multi-
ple mobile fragments. This interpretation is based on obser-
vations of the fractured state of the source zones pre- and
post-fall, as well as the size and distribution of visible rock
fragments in the post-fall areas of accumulation, below the
source zone and adjacent to the track. An example of this
can be seen in Fig. 8 for White Canyon overhanging wedge
event. In these photos it is clear that the source rock mass
is heavily jointed and that the accumulation of material gen-
erated from the event is not a few large blocks but rather a
deposit of coarse granular material.
The presence of multiple mobile fragments means that
these events may be classified as fragmental rockfalls
(Hungr and Evans, 1988; Hungr et al., 2014). Hungr and
Evans (1988) originally proposed that for the case of frag-
mental falls, the movements of the most mobile fragments
in the fall are independent of each other. This suggests that
the modelling of these events as a volume of fractured ma-
terial is unnecessary, and instead single design blocks with
a specified average or maximum fragment volume could be
used. This is in contrast to the idea that larger volume rock
slope failures such as rock avalanches should be modelled
as granular flows rather than independent ballistic trajecto-
ries (Bourrier et al., 2013). The distinction between these two
types of motion is often discussed in relation to the volume of
material mobilized as part of the event, with larger volumes
(>103–104m3) suggested to show stronger interaction be-
tween individual fragments. A discussion of the various vol-
umes and classifications of rock slope failure relevant to the
transition between these two styles of motion is presented by
Corominas et al. (2017) and suggests that volume thresholds
and terminology for these types of events is not yet consistent
in the literature.
While rockfall events <1000 m3, such as those considered
in this study, may be described as having limited interaction
between mobile fragments, the use of a single design block is
not effective in cases where sufficiently large fragmental falls
might overwhelm ditches at the base of a slope. A schematic
overview of this process can be seen in Fig. 9. Material which
builds up in the ditch or other retaining structures may allow
trailing rockfall debris to roll out over the newly formed sur-
face. Additionally, a trailing fragment of rock may impact the
accumulated pile of debris with enough force to push some
fragments out onto the track. Simulation of the entire frag-
mental rockfall volume at once, as a moving mass of many
fragments, allows for important slope-stopping features such
as benches, gullies, and ditches to be filled, impacting the
runout of trailing rockfall material. Snapshots from a video
of a recorded fragmental rockfall, which filled a ditch and im-
pacted a section of railway in western Canada, can be seen
in Fig. 10. In this case, the leading portion of the rockfall
event was pushed forward by trailing material before it fully
came to rest in the ditch. Additionally, subsequent individual
rock fragments were able to run out into the track region as a
result of the catchment ditch being full.
The simulation of these events as single block falls would
produce unrealistic runout due to interaction with retaining
structures like ditches. In addition, the mobility of larger
falls is much different than smaller fragments, with signifi-
cantly higher potential energies at release, as well as larger
moments of inertia affecting rotation during runout. At track
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Z. Sala et al.: Simulation of fragmental rockfalls detected using terrestrial laser scans 2389
Figure 3. Site A. Visual overview of the 170 m3wedge sliding rockfall event detected at the Goldpan site between July and October 2016.
The event involved a large triangular slab of weathered and jointed rock mass which failed approximately 35 m above a rock shed which
is protecting the track at Goldpan. Site photos (a, b) of the source zone pre- and post-failure are shown. Change detection results of the
event are shown (c) with cool colours indicating material loss and warm colours indicating material accumulation. Material from the rockfall
accumulated on the bench of the mid-slope gully, as well as on top of the rock shed, with the majority of the material running out over the
shed and leaving the slope. The rockfall hull of the event extracted from the pre- and post-failure meshes is shown (d), as well as a stereonet
representation of the wedge sliding failure mode.
Figure 4. Site B. Visual overview of the 24 m3wedge sliding rockfall event detected at the White Canyon East site between May and July
2016. The event involved a large pseudo-cubic block of weathered and jointed rock mass which failed approximately 46 m above track level.
Site photos (a, b) of the source zone pre- and post-failure are shown. Change detection results of the event are shown (c) with cool colours
indicating material loss and warm colours indicating material accumulation. A small portion of the rockfall volume was retained in the gully
leading down to track level, with the majority of the accumulation taking place in the track-side ditch. The rockfall hull of the event extracted
from the pre- and post-failure meshes is shown (d), as well as a stereonet representation of the wedge sliding failure mode. It should be noted
that parts of the source rock mass also exhibited overhanging sections.
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